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Recent Posts - page 32

• Hallucinated Configs and False Knowledge — The Quiet Risk of Wrong Answers

  By mrjvvxxm on July 7, 2025 • ( 0 )

  

  Overview When we talk about AI risks, we often think of breaches, abuse, or direct manipulation. But one of the most common and underestimated threats is much quieter: hallucination — the confident generation of incorrect or misleading information by large… Read More ›

• LLMs and Insider Threats — When Employees Weaponize AI Internally

  By mrjvvxxm on June 19, 2025 • ( 0 )

  

  Overview The rise of large language models (LLMs) inside organizations has empowered employees to work faster — but it’s also created a new vector for insider threats.Disgruntled employees, malicious contractors, or careless users can now use internal AI tools to… Read More ›

• Weaponizing AI for Vulnerability Research — When Attackers Use LLMs to Find and Exploit Bugs

  By mrjvvxxm on June 18, 2025 • ( 0 )

  

  Overview Security researchers use AI to enhance vulnerability discovery — but so do attackers. The same tools that help defenders audit code and infrastructure are being repurposed by threat actors to discover exploitable bugs at scale. Welcome to the rise… Read More ›

• LLM-Powered Phishing — How AI Writes Convincing Lures at Scale

  By mrjvvxxm on June 17, 2025 • ( 0 )

  

  Overview Phishing has evolved from misspelled scams to socially engineered masterpieces, thanks to large language models (LLMs). Modern threat actors now use AI to generate hyper-personalized, convincing phishing messages in seconds — at a scale and quality previously impossible. With… Read More ›

• Hijacking AI Agents — From Helpful Assistant to Autonomous Threat

  By mrjvvxxm on June 16, 2025 • ( 0 )

  

  Overview AI agents are no longer static models — they are autonomous systems that plan, reason, and act across digital environments. Whether managing emails, deploying code, or navigating internal tools, these agents are often given privileged access and decision-making capabilities…. Read More ›

• Exfiltration via AI Channels — Hiding Data in AI Prompts and Outputs

  By mrjvvxxm on June 11, 2025 • ( 0 )

  

  Overview Modern security teams monitor emails, file uploads, and network traffic for signs of exfiltration — but AI models open up a new covert channel. By embedding data inside prompts or manipulating model outputs, attackers can sneak information out of… Read More ›

• AI in Malware — LLMs Embedded in Payloads and Toolchains

  By mrjvvxxm on June 11, 2025 • ( 0 )

  

  Overview AI was once a tool for defenders — helping classify malware, detect anomalies, and improve SOC workflows. But now, attackers are embedding language models directly into malware, enabling dynamic payloads, evasive scripting, and autonomous decision-making during intrusions. This new… Read More ›

• Autonomous Reconnaissance — How AI Agents Scout for Vulnerabilities Without Human Help

  By mrjvvxxm on June 9, 2025 • ( 0 )

  

  Overview Reconnaissance is the first phase of nearly every cyberattack — gathering information about systems, users, and infrastructure. Traditionally, this required a human attacker. But now, AI agents can automate and accelerate reconnaissance at scale, with alarming precision. Autonomous reconnaissance… Read More ›

• Synthetic Identity Fraud Powered by AI — Faking People with Language and Pixels

  By mrjvvxxm on June 6, 2025 • ( 0 )

  

  Overview Identity fraud is nothing new — but AI has made it terrifyingly scalable. From fake resumes to deepfake selfies, synthetic identities are now being crafted by generative models that produce convincing, fully fabricated humans: names, photos, voice, and background… Read More ›

• Model Denial of Service (MoDoS) — Overloading AI with Adversarial Input

  By mrjvvxxm on June 5, 2025 • ( 0 )

  

  Overview Denial-of-service attacks are a classic threat to servers and web infrastructure — but as AI models are deployed across APIs, apps, and agents, they too have become targets of disruption. Model Denial of Service (MoDoS) refers to attacks that… Read More ›

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